In this course you will become familiar with the ideas of the water-energy-food nexus and transdisciplinary thinking.
You will learn to see your community or country as a complex social-ecological system and to describe its water, energy and food metabolism in the form of a pattern, as well as to map the categories of social actors.
We will provide you with the tools to measure the nexus elements and to analyze them in a coherent way across scales and dimensions of analysis. In this way, your quantitative analysis will become useful for informed decision-making. You will be able to detect and quantify dependence on non-renewable resources and externalization of environmental problems to other societies and ecosystems (a popular ‘solution’ in the western world). Practical case studies, from both developed and developing countries, will help you evaluate the state-of-play of a given community or country and to evaluate possible solutions. Last but not least, you will learn to see pressing social-ecological issues, such as energy poverty, water scarcity and inequity, from a radically different perspective, and to question everything you’ve been told so far.
ACKNOWLEDGEMENT
Part of the results and case studies presented have been developed within two projects: MAGIC and PARTICIPIA. However, the course does not reflect the views of the funding institutions or of the project partners as a whole, and the case studies were presented purely with an educational and illustrative purpose.

This week is all about narratives, framing and complexity. You will see how different narratives affect quantitative assessments, and why numbers aren’t always right. We will delve deeper into the theoretical basis of complex systems, and propose alternative ways of doing sustainability analysis, through the use of grammars.

Taught By

Mario Giampietro

ICREA Research Professor

Andrea Saltelli

Guest researcher

Tarik Serrano

Post-Doc Researcher

Transcript

[MUSIC] Let's start now with Session B: The identity in Complex Systems. This session was to explain systemic ambiguity found when we define an identity for an element of a complex system. They refer to two different perception of what we are defined within an entity. A type and an instance of a type and the difference between a structure and a functional element of a system. Let's start with the very definition of identity. Identity, the word, comes from Latin. It means idem and idem, and that is "same and same". What happens is that this requires that a single time is double mapping of two things: one is observed as to map into something which is used as a reference type and this mapping has to be associated with the name. So for instance, if I'm using a label a dog, and then I can use this label to identify an instance of a dog. If I see a dog on the street, this is a dog. But at the same time, I have to use the same label, dog, for the meaning of the dog, to identify in my mind, what the dog means for me. And of course distributed by order. Since the whole story is very tricky and not perfectly clear, let's try to use an example. Let's imagine I see a dog on a beach, like this one, and then in order to know that this is a dog and not an elephant or a dinosaur, I have to recall what I mean for a dog in my mind. So this what I expect to see when I see something that should be a dog. So, when what I expect to see is the same is mapping it to what I'm experiencing, then I can say, this is a dog. So basically, the identity imply a triangulation between something which is expected, something which is experienced, and a record of information, which is used to label that particular perception. Okay, so this is the most theoretical slides of the lessons, so you have to bear with me if we can go through this. So you have a name, what a dog? Then a type, what you expect the dog to be, and then an instance, what you are looking at as a dog. So, the combination of the three brings semantics in, that the name has a meaning, and the meaning is, what you expect from a dog and this is useful because make possible for you to identify dogs. So on one side, the name is the language part, the syntax. The type is the meaning of it, the expected attributes, the instance is the external referent. What I am interacting with in the external world. This is important because when we are dealing with the external world, we are looking with instance that cannot be exactly what we are expecting. For instance, we could have a dog with three legs, or with just one one eye. Still, the instance will be different from what is expected. But if there are many other expected characteristics of that instance that map onto the set of attributes of a dog, we can say that is a dog even if it has three legs. So in conclusion, we can say a type is a predictable set of attributes associated with an identity. While an instance of a type is an entity expressing that attributes so that we can assume that it's a part of the type. The distinction with the type and instance of type is important because there are information that can only be referring to instances, it cannot be referring to type. For example, let's imagine that we're talking about a tornado. A tornado is a dissipative system and we can predict a lot of tornado. We can predict when they will form, we can make models about tornado. Something we cannot predict is whether the tornado will be rotating clockwise or anti-clockwise. This is a characteristic that cannot be observed in an instance of tornado. If you are looking at an instance of tornado this will be a rotating in one direction or another and this is a phenomenon as called path-dependency. The mega remain locked in, in the initial stochastic event that decided whether it was rotating clockwise or anti-clockwise and in a way is keeping record of what happened to him as long as remain alive. Why this is important? Because there are information that can be gathered about times. And when dealing with complex systems, that are organized in several levels, then you can define two typology of time, or of types. Structural types of types, they are referring to the structure or organization of a system. For example, let's imagine we have a natural heart of a human being and these, more or less, are very similar to each other unless you have some defect and you have some disease because there is a template, recorded information about how to produce them. Natural heart. And what happen is that we can do a mechanical heart. Done again, with the template, a guarantee, the old template I do, I have the same structural organization. On the contrary, I can have a definition of functional type as the mutual information, generated by the contest. In this case, let's imagine we have the circulatory system of a human being. The circulatory system is generating A set of expected characteristics for the structural element, it would go in that places. Play that role in the node. So, we can start making a distinction between a functional type, a template of structural type, and realization and of a structural type. The functional type is the expected attributes. That's the context as on other parts. The natural heart is the characteristic, they're given to the structure because of the process of the obligation, and in this case you can see that we can have a bifurcation in the mapping. In this sense, you can have two different structural types, can go and perform the same role in the same function at all times. This is one of the first problems that you'll get with science, that you'll start getting, that when you're saying heart, a functional heart, [INAUDIBLE] because you could have a functional heart operating on a natural heart or a mechanical heart. In general this is a phenomenon that is expected every time you have a system organized on the circulatory hierarchical level. At one particular level, the circulatory system is a structural element of the human body. When you go inside a circular system, the circulatory system is generating a natural network niche for individual nodes inside n, and the network niche defines the admissibility of structural types. Just to see, this is a more plain terms. This is a metabolic network. So, whatever entry in A going C, B, E, D. At a certain point, I take out the element B, is a structural element. Still, the rest of the network has an image of the B there. And this is what can be done by a structural element put in that place. So for instance, in an ecosystem, you will have herbivores defined by a set relation between the primary producer and the carnivores. But then, we need the nodes of the functional nodes, of the animals. You could have different structural elements, protection of rabbits, of deers, of mice. And then, they can be adjusted, a different combination as long as the input and output at the level of the niche remain compatible with the context. Okay, so then we go into the conclusion of this session is that science can deal all with types and whereas the external world made of instance of types. So, we are trying to use genetic representation for process that are special. So there are external reference situations that are stable because the context is stable. So, then you're doing a functional type is what is called top-down causality. The context is forcing what the structural element can do, or you have a causality determined by the organization of the structural type. It would be bottom up causality. A functional element has a role to be expressed. So, a functional element has meaning only if it's expressed as a function, which is useful for the larger context. Whereas, a structural element doesn't have meaning as simply a composition and disposition to do things. Which is determined by the intrinsic organization reflecting the process of production. This is very important because it tells you that within a complex system, you have two completely different logic in what define the visibility and viability of the system. One structural type can only do things that reflect its composition and disposition. But if the structural type doesn't match the expectation of this context, it will not be countable of being part of the whole. In the same way, if the functional type requirement cannot be achieved or performed by the structural element, the context will no longer remain stable. So you are sort of ying-yang or in predicative relation, between the casuality imposed by the whole system to the part, in that causality goes into the characteristic part, to the system.

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